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Special Topics: Programming Languages Lecture #11 • 0 V22.0490.001 Special Topics: Programming Languages B. Mishra New York University. Lecture # 11 Programming Languages • MISHRA 2008 Lecture #11 • 1 —Slide 1— Common Lisp Language Survey 4 Functional Programming • Pure Functional Programming: Implicit Principle ◦ The value of an expression depends only on the values of its subexpressions, if any. – No side-effect. (No State—No assignment) – An expression has the same value, every time. – Implicit Storage Management: Allocation on Demand + Garbage Collection. – Functions are First Class Objects: 1) As value of an expression 2) As parameters 3) As data Objects. Programming Languages • MISHRA 2008 Lecture #11 • 2 —Slide 2— Common Lisp • LISP: LIst Processing Language Not— Lots of Insidious Sill Parentheses • Second oldest Programming Language (Af- ter Fortran) • Application Areas: 1. Theorem Proving 2. Symbolic Algebra 3. AI (Artificial Intelligence) (Natural Language Processing, Com- puter Vision, Robot Control Systems, Ex- pert Systems, Neural Networks, Automatic Programming) Programming Languages • MISHRA 2008 Lecture #11 • 3 —Slide 3— HISTORY • Developed at MIT AI Lab—1959. LISP 1.5 running on an IBM machine. • BBN LISP (PDP 1/SDS 940) became → INTERLISP (PDP 10) • MACLISP (MIT Project MAC) • LISP 1.6—A version of MACLISP ◦ UCI-LISP (Univ. of Cal. at Irvine) ◦ Standard Lisp (Univ. of Utah) • Lisp Machine Lisp Large Personal Lisp Machine built at MIT • FranzLISP for Vax/UNIX (UC Berkeley) • NIL for Vax/VMS (MIT) • Scheme at MIT • T Lisp at Yale Programming Languages • MISHRA 2008 Lecture #11 • 4 —Slide 4— Common Lisp • 1981/Carnegie-Mellon/Guy L. Steele • Clean Lisp Inconsistencies and illogical conventions were resolved • Transportable Programs written in Common Lisp and debugged in one implementation should run on another ma- chine/implementation without change. Programming Languages • MISHRA 2008 Lecture #11 • 5 —Slide 5— Lisp Data & Functional Objects • Lisp Programs and the data have Same form ◦ Self-modifying Lisp programs. ◦ Embedded languages in Lisp • Lisp functions are data objects that can be passed as parameters to other functions ◦ Extensible control structures • Interpreter + Compiler • Garbage Collector Programming Languages • MISHRA 2008 Lecture #11 • 6 —Slide 6— Lisp Objects • Lisp Objects 1. ATOMS (a) Numbers: {3, −5.7, 2010014567} (b) Symbols: { A, EVAL, PI, T, NIL } 2. CONS Conjunctions of two Lisp objects. Each of them may be a CONS object or an ATOM. • Example (CONS ’A ’B) (CONS ’2 (CONS ’BAD ’NIL)) Programming Languages • MISHRA 2008 Lecture #11 • 7 —Slide 7— CONS Cells = =Two Compartments... Each compartment holds an atom or a cons object (A pointer to a cons cell. (CONS 'B 'NIL) B NIL (B) (CONS 'A 'B) A B (A . B) (CONS '2 (CONS 'BAD 'NIL)) (2 BAD) 2 BAD NIL (CONS 'A (CONS (CONS 'B (CONS 'C 'NIL)) (CONS 'D NIL) ) A D NIL B C NIL (A (B C) D) Programming Languages • MISHRA 2008 Lecture #11 • 8 —Slide 8— LISTS • Function LIST (LIST ’A (LIST ’B ’C) ’D) => (A (B C) D) A D NIL B C NIL (A (B C) D) (LIST ’B NIL) => (B NIL) B NIL NIL (LIST) => NIL (An Atom not a CONS cell) Programming Languages • MISHRA 2008 Lecture #11 • 9 —Slide 9— Proper and Improper Lists • Proper Lists Lists terminating in NIL • Improper Lists Lists not terminating in NIL (A (B C) . D) A D B C NIL Programming Languages • MISHRA 2008 Lecture #11 • 10 —Slide 10— List Operations • CAR: Extracts the first element of a list • CDR: Extracts the rest (all but the first element) of a list • CAR & CDR can be applied to any list, but not to atom other than NIL (CAR NIL) ≡ (CDR NIL) ≡ NIL • Examples (CAR’(ABC)) =>A (CDR’(ABC)) =>(BC) (CAR (CDR (CAR (CDR ’(A (B C) D))))) => C Programming Languages • MISHRA 2008 Lecture #11 • 11 —Last Slide— List Predicates • Boolean-valued functions {T = True, NIL = False } • ATOM: True iff an atom (ATOM’NIL) => T (ATOM’(XY)) => NIL • CONSP, LISTP, ... • NULL: True iff an empty list (e.g., NIL) (NULL’NIL) => T (NULL’X) => NIL • ZEROP, NUMBERP, ... [End of Lecture #11] Programming Languages • MISHRA 2008.
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